Estimating a “quality” of a baseband video (i.e., frames and/or fields and/or sub-portions of frames/fields) or images or audio signals (i.e., pixel domains, not bitstreams) that may have been previously compressed and then subsequently decompressed using transformed-based techniques is difficult. Further difficulties arise in estimating what quantizer or maximum quantizer was applied to the video/image/audio signals if the baseband signals were previously compressed and then decompressed in multiple previous generations. The absence of compression information in the baseband signals leaves the blockiness of the video/image signals and the amount of mosquito noise (i.e., Gibbs artifacts) in video/image signals hard to estimate quantitatively.
Existing techniques to estimate the quantizer qualities and/or quantities from baseband signals use comparisons of pixels and/or sample differences at different regular intervals (i.e., modulo the suspected transform-size) in a pixel/sample domain. However, the existing techniques are easily confused by edges existing in the content itself. Therefore, the existing techniques are inaccurate. Furthermore, the existing techniques are incapable of providing any kind of accurate estimation of quantizer values, let alone accurate tracking of the quantizer values over time as rate-control varies the quantizer values while compressing. A practical disadvantage is that if the estimated quality (i.e., blockiness/quantizer/quality) is used for processing of the baseband signal, then poor results are commonly obtained.